Disentangling the Impacts of Environmental Contamination from
Download
1 / 33

Disentangling the Impacts of Environmental Contamination from Locally Undesirable Land-uses (LULUs) on Residential Pr - PowerPoint PPT Presentation


  • 87 Views
  • Uploaded on

Disentangling the Impacts of Environmental Contamination from Locally Undesirable Land-uses (LULUs) on Residential Property Values. Xiangping Liu, Laura Taylor, and Daniel Phaneuf June 25, 2010. Literature on Environmentally Contaminated Sites.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Disentangling the Impacts of Environmental Contamination from Locally Undesirable Land-uses (LULUs) on Residential Pr' - cybele


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Disentangling the Impacts of Environmental Contamination from Locally Undesirable Land-uses (LULUs) on Residential Property Values

Xiangping Liu, Laura Taylor, and Daniel Phaneuf

June 25, 2010


Literature on environmentally contaminated sites
Literature on Environmentally from Contaminated Sites

  • Use distance to a site listed on National Priority List (NPL) to proxy its impact

  • Study a single or several NPL sites in one area

    • Summarized in Kiel and Williams (2007)


Literature on environmentally contaminated sites contd
Literature on Environmentally from Contaminated Sites, contd.

  • Heterogeneity of the impact by site

    • Kiel and Williams (2007; all NPL sites)

  • Stigma

    • Messer et al. (2006)

    • McCluskey and Rausser (2003)

    • Dale et al. (1999)


Our contribution
Our Contribution from

  • Particular focus is to separate two impacts:

    • Contamination/cleanup (listing/delisting)

    • LULU (commercial or industrial properties)

  • Control for sites that are on both federal and state priority lists


Our contribution contd
Our Contribution, contd. from

  • Use accurate site boundary rather than the centroid

  • Estimate heterogeneous impacts of site types

    • Commercial vs. industrial sites

    • Landfill, solvent, and military sites vs. other sites

  • Use parcel-level transaction data, with careful attention to local unobservable community characteristics


Identification strategy geographic matching
Identification strategy--geographic matching from

  • Key issue: identify treated group & construct unobserved counterfactual for the treated observations.

  • Distance matters, but distance can be correlated with local unobservable characteristics.

    • Local community characteristics, if not controlled for, could bias the estimation.


Identification strategy contd
Identification strategy, contd. from

  • Treated observations:

    • Residential properties within 0.3-mile buffer to the boundary of a listed site

    • Identify land-use of each listed site

  • Control observations:

    • Residential properties within 0.3-mile buffer to the boundary of a clean commercial/industrial (COM/IND) site

    • Identify land-use of each “clean” site

  • Match clean COM or IND sites to contaminated sites based on their spatial locations


Identification strategy geographic matching1
Identification strategy--geographic matching from

  • Match treated & control observations based on their spatial locations:

    • Treated residential properties are within 0.3 mile buffer of listed site



Identification strategy geographic matching2
Identification strategy--geographic matching from

  • Match treated & control observations based on their spatial locations:

    • Treated residential properties are within 0.3 mile buffer of listed site

    • Create buffer ring of 0.7-1.0 mile from boundary of listed site



Identification strategy geographic matching3
Identification strategy--geographic matching from

  • Match treated & control observations based on their spatial locations:

    • Treated residential properties are within 0.3 mile buffer of listed site

    • Create buffer ring of 0.7-1.0 mile from boundary of listed site

    • Any “clean” commercial/industrial site lying within buffer ring serves as a control com/ind site



Identification strategy geographic matching4
Identification strategy--geographic matching from

  • Match treated & control observations based on their spatial locations:

    • Treated residential properties are within 0.3-mile buffer of listed site

    • Create buffer ring of 0.7-1.0 mile from centroid of listed site

    • Any “clean” commercial/industrial site lying within buffer ring serves as a control com/ind site

    • Control residential properties are within 0.3-mile buffer of control com/ind site



Identification strategy geographic matching5
Identification strategy--geographic matching from

  • Match treated & control observations based on their spatial locations:

    • Treated residential properties are within 0.3-mile buffer of listed site

    • Create buffer ring of 0.7-1.0 mile from centroid of listed site

    • Any “clean” commercial/industrial site lying within buffer ring serves as a control com/ind site

    • Control residential properties are within 0.3-mile buffer of control com/ind site



Heterogeneous effects and local community level unobservable
Heterogeneous effects and local community level unobservable from

  • Conduct analysis for COM and IND sites separately

  • Examine the impact by site types, eg. landfill, solvent, military sites, and other sites separately

  • Control for site fixed effect

    • Check the robustness of the result by controlling both site fixed effect and local community characteristics


Data from

  • Study area: Minneapolis/St. Paul metropolitan statistical area, Minnesota

  • Contaminated sites: All sites listed on state or federal registers of contaminated sites.

    • 108 sites (51 listed after 1990 / 59 delisted after 1990)

    • Site boundaries (manual identification)

    • Land-use

    • Contaminate type

  • Residential property transactions 1990-2007

    • housing attributes: acres, # rooms, bedrooms, baths, age, school district.


Data from

  • Community characteristics:

    • Census demographics at block group level are compiled from Geolytics

  • Local land-use characteristics (within 0.5 miles or 1 mile)

    • % land in: commercial use; industrial use; residential use; apartments, open space, water, highway


Example of treated control residential properties

Legend from

Control residential

Listed sites

Treated residential

Clean com/ind

Example of treated & control residential properties


Empirical specification
Empirical specification from

  • Mathematical representation of estimating equations

    --Listing

    Ln(sales price)=α*treat+β*tl+γ*treat_tl

    +constant+α*X+ site fixed effect+ time effect…

    --De-listing

    Ln(sales price)=α*treat+β*tdl+γ*treat_tdl

    +constant+α*X+ site fixed effect+ time effect…


Preliminary sample results listing
Preliminary sample results: listing from

  • All listed sites, no impact heterogeneity in land-use of site


Preliminary sample results: listing, continued. from

  • Heterogeneity by land-use: Commercial versus Industrial (all covariates & most recent transaction)


Preliminary sample results: de-listing from

All de-listed sites, no impact heterogeneity in land-use of site


Preliminary sample results: de-listing, continued from

  • Heterogeneity by land-use: Commercial versus Industrial (all covariates & most recent transaction)


Preliminary sample results: landfill, solvent, from military sites separately

  • Heterogeneity by site types: Landfills, solvent sites and military sites (all covariates & most recent transaction)


Conclusion
Conclusion from

  • The effect of contamination--listing a site reduces nearby residential property value 3-7 %

  • The listing has larger impact on residential property surrounding a industrial site than a commercial site

    • about 7-12% for a COM site

    • 47% an IND site

  • Delisting some NPL/PLP sites improves nearby residential property by 5%.

  • However, there exist stigma effect of cleanup on the nearby residential property for the landfill sites.


Work to do
Work-to-do from

  • Matching NPL/PLP sites based on local community characteristics rather than geographical location (a propensity score matching or matching on local community characteristics directly). This method allows us to further check how strong local community characteristics or unobservables affect estimation results.

  • Separate regressions for detached residential properties, townhouse, and condo


The end thank you
The End from Thank you!


Preliminary sample results: de-listing, continued from

  • Heterogeneity by land-use: Commercial versus Industrial (all covariates & most recent transaction)


Preliminary sample results: de-listing, continued from

De-listed sites, exluding landfill, solvent & military sites


Preliminary sample results: de-listing, continued from

De-listed sites, only landfill, solvent & military sites


ad